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变转速工况下高速列车轴承转子系统特性分析

王宝森 刘永强 张斌

王宝森, 刘永强, 张斌. 变转速工况下高速列车轴承转子系统特性分析. 力学学报, 2022, 54(7): 1-14 doi: 10.6052/0459-1879-22-067
引用本文: 王宝森, 刘永强, 张斌. 变转速工况下高速列车轴承转子系统特性分析. 力学学报, 2022, 54(7): 1-14 doi: 10.6052/0459-1879-22-067
Wang Baosen, Liu Yongqiang, Zhang Bin. Characteristics analysis on bearing rotor system of high-speed train under variable speed conditions. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(7): 1-14 doi: 10.6052/0459-1879-22-067
Citation: Wang Baosen, Liu Yongqiang, Zhang Bin. Characteristics analysis on bearing rotor system of high-speed train under variable speed conditions. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(7): 1-14 doi: 10.6052/0459-1879-22-067

变转速工况下高速列车轴承转子系统特性分析

doi: 10.6052/0459-1879-22-067
基金项目: 国家重点研发计划(2020YFB2007700)、国家自然科学基金(11790282, 12032017, 12002221, 11872256)、河北省科技计划(20310803D), 河北省自然科学基金(A2020210028), 河北省教育厅科技计划(ZD2021093)和留学基金委资助项目
详细信息
    作者简介:

    刘永强, 教授, 主要研究方向: 车辆系统动力学, 预测和健康管理. E-mail: liuyq@stdu.edu.cn

  • 中图分类号: U270.1 + 1

CHARACTERISTICS ANALYSIS ON BEARING ROTOR SYSTEM OF HIGH-SPEED TRAIN UNDER VARIABLE SPEED CONDITIONS

  • 摘要: 高速列车的发展使得其关键零部件—轴承的安全问题日益突出. 现有的轴承模型均是建立在匀速工况下, 不能描述系统在变转速工况下运动状态. 为了解决这个问题, 建立了一个变转速工况下高速列车轴箱轴承转子系统动力学模型, 模型通过角度迭代计算得到了滚动体在不均匀时间内转过的总角度, 进而确定了滚动体在任意时刻的空间位置. 在匀速工况和变转速工况下, 对具有外圈故障的轴承模型进行了实验对比, 验证了模型的有效性. 利用轴心轨迹定性分析了外圈故障、内圈故障和滚动体故障对系统稳定性的影响, 并通过实验验证了分析结果的可靠性. 利用二维不变矩作为特征指标定量分析了三类故障对系统稳定性的影响. 分析结果表明: 当轴承角加速度较小时, 外圈故障对系统稳定性影响最大; 当轴承角加速度较大时, 滚动体故障对系统稳定性影响最大, 但是影响程度随着故障尺寸的变大而逐渐减小. 同样地, 利用二维不变矩作为特征指标进行了系统的稳定性临界状态分析, 确定了在不同转速工况下和不同故障类型下临界状态对应的最大故障尺寸. 研究结果表明: 随着轴承内圈转速的上升, 不同故障类型对应的最大尺寸都会减小, 其中滚动体故障尺寸大都是最小的, 说明滚动体故障对系统稳定性影响最大.

     

  • 图  1  轴承转子系统模型

    Figure  1.  Model of bearings and rotor coupling system

    图  2  轴承侧视图

    Figure  2.  Side view of the bearing

    图  3  轴承动力学模型

    Figure  3.  Bearing dynamics model

    图  4  轴承外圈、外圈故障和内圈故障示意图

    Figure  4.  The schematic diagram of the outer ring, the outer ring fault and the inner ring fault

    图  5  实验台和传感器安装位置示意图

    Figure  5.  The schematic diagram of the test rig and sensors’ location

    图  6  匀速工况下的仿真结果

    Figure  6.  Simulation results under constant speed condition

    图  7  匀速工况下的实验结果

    Figure  7.  Experimental results under constant speed condition

    图  8  变转速工况下的实验结果

    Figure  8.  Experimental results under variable speed condition

    9  变转速工况下的仿真结果

    9.  Simulation results under variable speed condition

    图  10  转子处轴心轨迹

    Figure  10.  Axis trajectory diagram at the rotor

    图  11  轴承处轴心轨迹

    Figure  11.  Axis trajectory diagram at the bearing

    图  12  外圈故障条件下对比结果

    Figure  12.  Results comparison under the condition of outer ring fault

    图  13  内圈故障条件下对比结果

    Figure  13.  Results comparison under the condition of inner ring fault

    图  14  轴承处轴心轨迹的φ1φ2的值

    Figure  14.  Values of φ1 and φ2 of axis trajectory at bearing

    15  转子处轴心轨迹的φ1φ2的值

    15.  Values of φ1 and φ2 of axis trajectory at rotor

    15  转子处轴心轨迹的φ1φ2的值(续)

    15.  Values of φ1 and φ2 of axis trajectory at rotor (continued)

    图  16  三种角加速度下转子处轴心轨迹

    Figure  16.  axis trajectory at rotor under the conditions of three angular accelerations

    图  17  不同转速条件下φ1,ORF,rotor随故障尺寸的变化规律

    Figure  17.  Variation of φ1,ORF,rotor with fault size at different rotating speeds

    表  1  轴承几何参数

    Table  1.   Geometric parameters of the bearing

    ParameterValue
    Mass of the inner ring m1/kg 4.63
    Inner ring radius r/mm 65
    Total mass of the bearing m2/kg 30
    Outer ring radius R/mm 120
    Numbers of roller N0 17
    Average roller diameter d/mm 26.5
    Pitch diameter D/mm 156.25
    Load F/N 7.0205 × 104
    下载: 导出CSV

    表  2  轴承系统模型参数

    Table  2.   Parameter of the bearing system model

    ParameterValue
    Axle equivalent mass mc/kg 274
    Stiffness of axle C/(N·s·m−1) 2 × 103
    Damping of axle K/(N·m−1) 1.48 × 107
    Mass eccentricity of axle section e/mm 10-5
    Stiffness of inner ring C1/(N·s·m−1) 7 × 104
    Damping of inner ring K1/(N·m−1) 3.05 × 108
    Stiffness of outer ring C2/(N·s·m−1) 7 × 104
    Damping of outer ring K2/(N·m−1) 2 × 1010
    Contact damping Kt/(N·m−1) 3.5 × 1010
    下载: 导出CSV

    表  3  单元谐振器参数

    Table  3.   The parameter of the unit resonator

    ParameterValue
    Mass mb/kg1
    Damping Kb/(N·m−1)8.8826 × 109
    Stiffness Cb/(N·s·m−1)9.424 × 103
    下载: 导出CSV

    表  4  不同转速条件下稳定性临界状态对应的最大故障尺寸

    Table  4.   Maximum fault size corresponding to stability critical state under different speed conditions

    Fault typesBearing angular speed/(r·min−1)
    100600110016002100
    Inner ring fault0.990.760.650.910.53
    Roller fault0.420.781.030.680.23
    下载: 导出CSV
  • [1] 伏培林, 丁立, 赵吉中等. 考虑材料温度相关性的二维轮轨弹塑性滑动接触温升分析. 力学学报, 2020, 52(5): 1245-1254 (Fu Peilin, Ding Li, Zhao Jizhong, et al. Frictional temperature analysis of two-dimensional elasto-plastic wheel-rail sliding contact with temperature-dependent material properties. Chinese Journal of Theoretical and Applied Mechanics, 2020, 52(5): 1245-1254 (in Chinese) doi: 10.6052/0459-1879-20-122
    [2] 李德发, 齐红元, 侯东明等. 动车组轴箱轴承状态的声发射检测机理研究. 机械工程学报, 2021, 57(12): 153-160 (Li Defa, Qi Hongyuan, Hou Dongming, et al. Research on acoustic emission detection mechanism of axle box bearing state of EMU. Journal of Mechanical Engineering, 2021, 57(12): 153-160 (in Chinese) doi: 10.3901/JME.2021.12.153
    [3] Rai VK, Mohanty AR. Bearing fault diagnosis using FFT of intrinsic mode functions in Hilbert–Huang transform. Mechanical systems and signal processing, 2007, 21(6): 2607-2615 doi: 10.1016/j.ymssp.2006.12.004
    [4] 乔志城, 刘永强, 廖英英. 改进经验小波变换与最小熵解卷积在铁路轴承故障诊断中的应用. 振动与冲击, 2021, 40(2): 81-90 + 118 (Qiao Zhicheng, Liu Yongqiang, Liao Yingying. Application of improved wavelet transform and minimum entropy deconvolution in railway bearing fault diagnosis. Journal of Vibration and Shock, 2021, 40(2): 81-90 + 118 (in Chinese)
    [5] Cvetkovic Z. On discrete short-time Fourier analysis. IEEE transactions on signal processing, 2000, 48(9): 2628-2640 doi: 10.1109/78.863068
    [6] McInerny SA, Dai Y. Basic vibration signal processing for bearing fault detection. IEEE Transactions on education, 2003, 46(1): 149-156 doi: 10.1109/TE.2002.808234
    [7] Li YB, Xu MQ, Liang XH, et al. Application of bandwidth EMD and adaptive multiscale morphology analysis for incipient fault diagnosis of rolling bearings. IEEE Transactions on Industrial Electronics, 2017, 64(8): 6506-6517 doi: 10.1109/TIE.2017.2650873
    [8] Shang ZW, Liu X, Liao XX, et al. Rolling bearing fault diagnosis method based on EEMD and GBDBN. International Journal of Performability Engineering, 2019, 15(1): 230-240
    [9] 王茜, 田慕琴, 宋建成等. 基于经验小波变换的振动信号特征量提取. 振动与冲击, 2021, 40(16): 261-266 (Wang Qian, Tian Muqin, Song Jiancheng, et al. Feature extraction of vibration signals based on empirical wavelet transform. Journal of Vibration and Shock, 2021, 40(16): 261-266 (in Chinese)
    [10] 董绍江, 裴雪武, 吴文亮等. 基于多层降噪技术及改进卷积神经网络的滚动轴承故障诊断方法. 机械工程学报, 2021, 57(1): 148-156 (Dong Shaojiang, Pei Xuewu, Wu Wenliang, et al. Rolling bearing fault diagnosis method based on multilayer noise reduction technology and improved convolutional neural network. Journal of Mechanical Engineering, 2021, 57(1): 148-156 (in Chinese) doi: 10.3901/JME.2021.01.148
    [11] Sun JD, Yan CH, Wen JT. Intelligent bearing fault diagnosis method combining compressed data acquisition and deep learning. IEEE Transactions on Instrumentation and Measurement, 2017, 67(1): 185-195
    [12] Shao HD, Jiang HK, Zhang HZ, et al. Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing. Mechanical Systems and Signal Processing, 2018, 100(1): 743-765
    [13] McFadden PD, Smith JD. Model for the vibration produced by a single point defect in a rolling element bearing. Journal of sound and vibration, 1984, 96(1): 69-82 doi: 10.1016/0022-460X(84)90595-9
    [14] Rafsanjani A, Abbasion S, Farshidianfar A, et al. Nonlinear dynamic modeling of surface defects in rolling element bearing systems. Journal of Sound and Vibration, 2009, 319(3-5): 1150-1174 doi: 10.1016/j.jsv.2008.06.043
    [15] 陈果. 航空发动机整机耦合动力学模型及振动分析. 力学学报, 2010, 42(3): 548-559 (Chen Guo. Coupling dynamic model and dynamic analysis for whole aero-engine. Chinese Journal of Theoretical and Applied Mechanics, 2010, 42(3): 548-559 (in Chinese) doi: 10.6052/0459-1879-2010-3-2008-706
    [16] 曹青松, 郭小兵, 熊国良等. 高速列车滚动轴承支承松动系统动力学特性研究. 机械工程学报, 2016, 52(21): 87-95 (Cao Qingsong, Guo Xiaobing, Xiong Guoliang, et al. Study on Dynamic Characteristics of High-speed Train Rolling Bearing with Pedestal Looseness. Journal of Mechanical Engineering, 2016, 52(21): 87-95 (in Chinese) doi: 10.3901/JME.2016.21.087
    [17] Wang ZW, Zhang WH, Yin ZH, et al. Effect of vehicle vibration environment of high-speed train on dynamic performance of axle box bearing. Vehicle System Dynamics, 2019, 57(4): 543-563 doi: 10.1080/00423114.2018.1473615
    [18] 刘永强, 王宝森, 杨绍普. 含外圈故障的高速列车轴承转子系统非线性动力学行为分析. 机械工程学报, 2018, 54(8): 17-25 (Liu Yongqiang, Wang Baosen, Yang Shaopu. Nonlinear dynamic behaviors analysis of the bearing rotor system with outer ring faults in the high-speed train. Journal of Mechanical Engineering, 2018, 54(8): 17-25 (in Chinese) doi: 10.3901/JME.2018.08.017
    [19] Mishra C, Chakraborty G, Samantaray AK. Rolling element bearing fault modelling to develop a diagnosis scheme for oscillating and non-uniform shaft rotation//The First International and Sixteenth National Conference on Machines and Mechanisms, Roorkee, 2013-12-18-20. Cambridge: Cambridge University Press, 2013: 86-94
    [20] Mishra C, Samantaray AK, Chakraborty G. Bond graph modeling and experimental verification of a novel scheme for fault diagnosis of rolling element bearings in special operating conditions. Journal of Sound and Vibration, 2016, 377: 302-330 doi: 10.1016/j.jsv.2016.05.021
    [21] 王曦, 侯宇, 孙守光等. 高速列车轴承可靠性评估关键力学参量研究进展. 力学学报, 2021, 53(1): 19-34 (Wang Xi, Hou Yu, Sun Shouguang, et al. Advances in key mechanical parameters for reliability assessment of high-speed train bearings. Chinese Journal of Theoretical and Applied Mechanics, 2021, 53(1): 19-34 (in Chinese)
    [22] 倪振华. 振动力学. 西安: 西安交通大学出版社, 1988: 52-56

    Ni Zhenhua. Vibration Mechanics. Xi’an: Xi’an Jiaotong University Press, 1988: 52-56 (in Chinese)
    [23] Qin Yi, Cao Folin, Wang Yi, et al. Dynamics modelling for deep groove ball bearings with local faults based on coupled and segmented displacement excitation. Journal of Sound and Vibration, 2019, 447: 1-19 doi: 10.1016/j.jsv.2019.01.048
    [24] 吴飞科. 圆锥滚子轴承接触应力分析及凸度设计. [硕士论文]. 河南河南科技大学, 2007

    Wu Feike. Analysis on contact stress of tapered roller bearings and crowning design. [Master’s thesis]. Henan: Henan University of science and technology, 2007(in Chinese))
    [25] Ma Liang, Zhang Junhong, Lin Jiewei, et al. Dynamic characteristics analysis of a misaligned rotor-bearing system with squeeze film dampers. Journal of Zhejiang University-Science A, 2016, 17(8): 614-631 doi: 10.1631/jzus.A1500111
    [26] Cui LL, Zhang Y, Zhang FB, et al. Vibration response mechanism of faulty outer race rolling element bearings for quantitative analysis. Journal of Sound and Vibration, 2016, 364: 67-76 doi: 10.1016/j.jsv.2015.10.015
    [27] 吴昊, 王建文, 安琦. 圆柱滚子轴承阻尼的计算方法. 轴承, 2008, 9: 1-5 (Wu Hao, Wang Jianwen, An Qi. Calculating method for damping of cylindrical roller. Bearings, 2008, 9: 1-5 (in Chinese)
    [28] Huang Y, Lin JH, Liu ZC, et al. A modified scale-space guiding variational mode decomposition for high-speed railway bearing fault diagnosis. Journal of Sound and Vibration, 2019, 444: 216-234 doi: 10.1016/j.jsv.2018.12.033
    [29] Urbanek J, Barszcz T, Jablonski A. Application of angular–temporal spectrum to exploratory analysis of generalized angular–temporal deterministic signals. Applied Acoustics, 2016, 109: 27-36 doi: 10.1016/j.apacoust.2016.03.004
    [30] 高冠琪, 黄伟国, 李宁等. 基于时频挤压和阶比分析的变转速轴承故障检测方法. 振动与冲击, 2020, 39(3): 205-210 + 226 (Gao Guanqi, Huang Weiguo, Li Ning, et al. Fault detection method for varying rotating speed bearings based on time-frequency squeeze and order analysis. Journal of Vibration and Shock, 2020, 39(3): 205-210 + 226 (in Chinese)
    [31] Yang Y, Peng ZK, Meng G, et al. Spline-kernelled chirplet transform for the analysis of signals with time-varying frequency and its application. IEEE Transactions on Industrial Electronics, 2011, 59(3): 1612-1621
    [32] Hu MK. Visual pattern recognitions by moment invariants. IRE Transactions on Information Theory, 1962, 8(2): 179-187 doi: 10.1109/TIT.1962.1057692
    [33] 丁悦, 吴静静, 蒋毅等. 基于改进HU不变矩的快速图像匹配算法. 传感器与微系统, 2020, 39(2): 124-127 (Ding Yue, Wu Jingjing, Jiang Yi, et al. Fast image matching algorithm based on improved HU invariant moment. Transducer and Microsystem Technologies, 2020, 39(2): 124-127 (in Chinese)
    [34] 郭哲, 张艳宁, 林增刚. 基于扩展二维不变矩的三维人脸特征提取. 吉林大学学报(工学版), 2012, 42(2): 446-450

    Guo Zhe, Zhang Yanning, Lin Zenggang, 3 D face feature extraction based on extended 2 D invariant moment. Journal of Jilin University (Engineering and Technology Edition), 2012, 42(2): 446-450(in Chinese))
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  • 收稿日期:  2022-02-13
  • 录用日期:  2022-04-25
  • 网络出版日期:  2022-04-26

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